GraphScope v0.3.0 is released as scheduled. This release includes new features and major updates for frontend APIs for graph manipulation, integration with other systems as well as code optimization for some operators. Another direction we are working on is to ease the deployment of GraphScope with/without Kubernetes.
We highlight the following improvements included in this release:
Better integration with other systems
- GraphScope aims to support easy integrations with other big data processing systems. As a first step, this release supported that the results (in the format of dataframe) of GraphScope can be further processed by Mars, a distributed tensor-based computation engine.
Performance and function enhancement
- Pre-compile a set of commonly used applications and graphs into the docker image to improve the response time of each operation in Python.
- Optimize the implementation of
- Support Louvain algorithm as a built-in application in the graph analytics engine.
Improved graph manipulation APIs
- Support for adding vertices and edges to an existing graph.
- Add a general project operator.
Easier deployment with/without Kubernetes.
For more detailed improvements that have been made in this release, please refer to the complete changelog.